A distribution management system (DMS) for an electric power distribution system identifies fault locations by pattern matching between measured fault current(s) and predicted fault currents using a system model of the distribution network and hypothesized fault location, types, and fault impedances. Conventional symmetrical component-based methods are not suitable for distribution systems that are unbalanced in both build and operation. Phase-based methods are needed for accurate analysis. However, the resulting system can be very large, even for average feeders, because of the large number of nodes resulting from explicit representation of individual phases. Impedance based methods are both memory-intensive and time-consuming. Admittance matrix-based methods are much more memory efficient, but time-consuming. Compensation-based and matrix inversion lemma-based methods purportedly reduce the computation burden associated with inverting the admittance matrix repeatedly. However, these conventional methods are computationally intensive for repeated fault analysis at many bus locations with various fault types and involve building and factorizing the admittance matrix, or even inverting the admittance matrix for each fault location and fault types. Also, traditional methods using symmetrical components can handle unbalanced fault, but not unbalanced network modeling.